How to Use Big Data in Freight Transportation?

“War is 90% information.” A quote well said by Napoleon Bonaparte in the 19th century that still holds the right judgment of truth. With businesses, enterprises and large MNC’s rushing to be the top players in their field, success holds to those who are well equipped with managed, organized and processed information. Big Data in freight transportation has been the current buzzword in the tech world and great industry minds have always welcomed the benefits of controlling their huge sets of raw information or data.

Be it analysis or integrating the statistical approach of harnessing the right information out of the raw data, Big Data and Data Analytics have curved the ways businesses have been since their inception. Organization leaders and senior corporate executives are able to learn more about their business, gather more insights and device better decisions based on facts and information.

What is Big Data?

Big Data, is a field in Data Science that deals with various processes of organizing and analyzing large, random and complex data sets in order to extract information that is useful. The current trends in the application of big data in freight transportation are utilizing user behavior analytics, predictive analytics, and any other forms of data extraction that bring value.

The collection and accumulation of raw data are done in bulk as they are collected through different information sensing devices like mobiles, tablets, software logs, remote sensing, RFID readers and even wireless sensor networks. However, collecting build information and not being able to extract the needed information and at the right time can be rather considered as a waste. This is when the application of Big Data comes into the picture.

Big Data revolutionizing logistics and freight transport the big way!

A colossal amount of data is generated every day as each shipper or customer prefers to ship their parcel or consignment through logistics. But it is not only about the amount of data that is being generated but also about the variety of data that needs to be organized. As defined by Gartner, Big Data is the analysis of the relation between high variety, high velocity and high volume information asset that intends to improve the decision making process with better insight and process automation.

Now, logistics and freight transport companies are service providers that make them deal with not only a large set of data about every parcel or freight but also a variety of freight data. This makes the entire network for globally operating logistics and freight service companies more complex to deal with. The transportation management system is known to increase freight capacity. This is where Big Data & analytics come into the picture. With big data and data, analytics tool business leaders can now process the endless array of unorganized data into meaningful business insights adding more value and streamlining service development. It has now become much easier to decide on the pricing strategy, product placement, shipment tracking, order and delivery reports, risk management, and a lot more.

Applications of Big Data in logistics

The conventional way of keeping records of important information like customer details, customer feedback, freight route details, review, and social media presence, etc were all maintained and calculated by human minds. With big data and data analytics making its strides into logistics, the industry has witnessed hordes of opportunities and room for further improvement. Here are a few ways to utilize this gift of technology.

Big data is used for predictive analysis for freight transportation. It helps the management to predict and estimate the volume of the freight according to days, weeks or months. This helps the business leaders to estimate and define and cost structure for future business operations.

Routes, effective communication, cost, and facilities are important attributes in the logistics industry. Big data allows data scientists to analyze large collected data and bring out necessary insights for better decision making process.

With all the valuable insights in hand, big data can be used as a tool to predict the time taken for each freight and therefore plan for further business accordingly.

Big data can also be used to track down the most rated or underrated feedback from the customer all across a huge market. This would also allow the logistics business to continuously develop their service to keep their customers satisfied.

Benefits of having Big Data in freight transportation

When it comes to benefits, Big data makes the longest tide among the latest technologies that provide in-depth business insight and other benefits.

Enhanced Knowledge

With a judicious amount of capabilities to extract the right and needed information out of a large and complex collection of raw data, Big Data has equipped all the business leaders with an arsenal of enhanced knowledge. The greater analytical power and authority to extract targeted information or statistics helped the businessmen to derive perfect campaign reports. The more knowledge that was being extracted and utilized, the authenticity and quality of the service or offerings went high.

Many standing logistics organization has already integrated the use of Big data into their business operations and have been sharing the amazing results. The technology has given a better insight into freight arrangements, current orders on a global range, cargo details, encrypt the entire routing network across every operating market. Besides, Big Data has not only helped organizations improve their way of interacting with their clients but has also ensured to have enhanced knowledge on every shipment.

Improved customer service

Well, with better insights and the tool to convert any form of data into the right information about any customer or client, decision-makers can better serve the needs of their target audience. This is one of the most important benefits big data has brought to the world of logistics and transportation. Using the analytical tools, businesses are now able to draw out more relevant information regarding any freight or consignment at any point in time.

At times, having more relevant information allows a business to respond promptly to customer queries, address any concern regarding the shipment and a lot more. The same goes for shippers or distributors. The logistics and freight transport industry can now keep a better track of the entire network and details of every shipper. Also, collecting and analyzing repetitive customer complaints to improve service and look into matters that need immediate attention.

Efficient Operation

As the flow of information helped business leaders to shape the course of their operations, Big Data added another benefit to them. In-depth analysis and thorough surveying of freights, consignments and parcels that are being dispatched to be transported reduce errors and chances of overlooks. This enhances the efficiency of business operations.

Deciding the fate of Big Data in the logistics industry

Big data, a gift of technology does seem to have long term implications and impact on the logistics industry. However, it is important for businesses integrating big data for the first time into their logistics operations to keep up with certain know-how to get the best out of this technology.

Another major concern that needs attention is data manipulation. With a large set of private and business data, and having access to all these data makes it easier for any data analyst to manipulate the data according to the needs of the company. This is mostly seen in terms of marketing and promotional activities. Businesses often use the power of big data to target marketing campaigns to people based on their own private data.

Conclusion

As the logistics industry deals with information and data about their customers, the major concern that arises is of data privacy. It is important for the data scientist and the stakeholders to have a mutual agreement about extracting any related information that can be subjected to privacy issues. This disintegrates the authenticity of the service industry and resets a negative impact on customers. These terms need to be sorted out before integrating the process which would also assist in performing risk management surveys.